A wearable medical monitoring device includes a plurality of ECG electrodes configured to receive an ECG signal when the wearable medical monitoring device is worn by a patient, and a monitor coupled to the plurality of ECG electrodes. The monitor is configured to detect an impending cardiac event based on the received ECG signal of the patient. The device includes at least one processor configured to execute a plurality of instructions to implement an update manager configured to receive a software update corresponding to the at least one software module for the monitor, determine an event estimation of risk score for a predetermined period of time, cause an installation of the update when the event estimation of risk score indicates a low likelihood of an impending cardiac event, and cause a delay in the installation when the event estimation of risk score indicates a high likelihood of impending cardiac event.

A method for time-synchronizing waveforms from different patient monitors that does not require devices to have high-precision synchronized clocks or to be coupled to a triggering synchronization signal generator. Comparable signals may be obtained from different devices either by placing selected sensors from the devices in the same locations, or by filtering signals from one device to obtain a signal comparable to signals from another device. Filtering may for example transform waveforms into independent components and identify a component that matches a signal from another device. The comparable signals may then be transformed into frequency variation curves, such as time intervals between peak values, to facilitate detection of the time shift between the signals. Cross correlation of the frequency variation curves may be used to locate the precise time shift between the signals. Use of frequency variation curves may be more robust than directly comparing and correlating the original signals.

A measurement station includes an electrocardiogram acquisition system, two control electrodes configured to contact a user, and an electrical connection circuit, the electrical connection circuit comprising a feedback loop connected to the two control electrodes.

A measurement station includes an electrocardiogram acquisition system, two control electrodes configured to contact a user, and an electrical connection circuit, the electrical connection circuit comprising a feedback loop connected to the two control electrodes.

The invention provides a multi-sensor system that uses an algorithm based on adaptive filtering to monitor a patient's respiratory rate. The system features a first sensor selected from the following group: i) an impedance pneumography sensor featuring at least two electrodes and a processing circuit configured to measure an impedance pneumography signal; ii) an ECG sensor featuring at least two electrodes and an ECG processing circuit configured to measure an ECG signal; and iii) a PPG sensor featuring a light source, photodetector, and PPG processing circuit configured to measure a PPG signal. Each of these sensors measures a time-dependent signal which is sensitive to respiratory rate and, during operation, is processed to determine an initial respiratory rate value. An adaptive digital filter is determined from the initial respiratory rate. The system features a second sensor (e.g. a digital 3-axis accelerometer) that attaches to the patient's torso and measures an ACC signal indicating movement of the chest or abdomen that is also sensitive to respiratory rate. This second signal is processed with the adaptive filter to determine a final value for respiratory rate.

A method, including receiving a bipolar signal from a pair of electrodes in proximity to a myocardium of a human subject, and receiving a unipolar signal from a selected one of the pair of electrodes. The method further includes delineating a window of interest (WOI) for the unipolar and bipolar signals, within the WOI computing local unipolar minimum derivatives of the unipolar signal, and times of occurrence of the local unipolar minimum derivatives, and within the WOI computing bipolar derivatives of the bipolar signal at the times of occurrence. The method also includes evaluating ratios of the bipolar derivatives to the local unipolar minimum derivatives, and when the ratios are greater than a preset threshold ratio value, assigning the times of occurrence as times of activation of the myocardium, counting a number of the times of activation; and classifying the unipolar signal according to the number.

A cardiovascular detection system and method, comprising an active compression cuff contracting at a frequency higher than the systolic frequency of the heart. Meanwhile, the detection device is used to capture the influence of the active compression cuff and cardiac systole on the blood of the part to be detected. In addition, it is supplemented by electrocardiography to monitor the reference value of cardiac systole to distinguish the difference between the pulse wave generated by the active compression cuff and the pulse wave generated by the heart. In this way, the state of the cardiovascular system can be quickly understood. Since the active compression cuff is contracted at a frequency higher than the systolic frequency of the heart, it can be more accurately determined whether the blood vessel is blocked or hardened.

A cardiovascular detection system and method, comprising an active compression cuff contracting at a frequency higher than the systolic frequency of the heart. Meanwhile, the detection device is used to capture the influence of the active compression cuff and cardiac systole on the blood of the part to be detected. In addition, it is supplemented by electrocardiography to monitor the reference value of cardiac systole to distinguish the difference between the pulse wave generated by the active compression cuff and the pulse wave generated by the heart. In this way, the state of the cardiovascular system can be quickly understood. Since the active compression cuff is contracted at a frequency higher than the systolic frequency of the heart, it can be more accurately determined whether the blood vessel is blocked or hardened.

The present invention relates to a medical device, in particular to an implantable medical device, comprising at least one implantable or non-implantable hemodynamic sensor configured for detecting hemodynamic cardiac signals, a controller configured for processing and analyzing the detected cardiac hemodynamic signals or signals derived from the detected cardiac hemodynamic signals by applying to said signals a Teager Energy Operator (TEO). The controller further comprises at least one algorithm configured to determine the need for a defibrillation operation by taking into account the at least one output hemodynamic signal. The present invention also provides a method and software for detecting or treating a ventricular fibrillation episode by taking into account cardiac hemodynamic signals.

A method of detecting changes in blood flow in a head of a subject includes measuring a value of a parameter of a cardiac bioelectrical signal at a scalp area of the subject relative to a reference cardiac bioelectrical signal. The method also includes comparing the value of the measured parameter with a predetermined value of the parameter to determine any change in blood flow in the head of the subject. The determined change can be used to detect changes in perfusion in the brain of a subject for example, as a result of anti-coagulation medication used to dissolve a clot in a blood vessel of the brain of a subject who has experienced ischaemic stroke.